ResuMatch - AI-Powered Resume-Job Matching Platform

🚀 Status: Live & Deployed
🌐 Production: https://resumatchh.xyz
📱 Frontend (Vercel): https://resumatch-front-4nts.vercel.app
🔧 Backend API: https://resumatch-backend-q5qo.onrender.com
🐳 Docker Hub: josephshibumathew/resumatch
🗄️ Database: MongoDB Atlas

🎯 Try It Now

🌐 Live Demo

Production: https://resumatchh.xyz (Secure HTTPS deployment)
Frontend: https://resumatch-front-4nts.vercel.app

📋 Test Features:

Student Experience:
- Create account → Upload resume → Get AI matches → Apply to jobs → Chat with recruiters
Recruiter Experience:
- Create account → Post jobs → Review applications → Chat with candidates
AI Features:
- Resume analysis with skill extraction
- Job matching algorithm
- Mock interview questions

🔧 API Access

Backend API: https://resumatch-backend-q5qo.onrender.com

Health Check: /healthz
Interactive Docs: /docs
OpenAPI Schema: /openapi.json

🌟 Overview

ResuMatch is an intelligent platform that connects students and recruiters through AI-powered resume analysis and job matching. The platform uses Groq's Llama 3.3 70B model to provide comprehensive resume analysis, generate enhanced resumes, and create job-specific tailored resumes to help students stand out in their applications.

🎯 New Two-Stage Resume Analysis System

Stage 1: Basic Resume Analysis (Immediate Value)

Upload your resume and get instant, comprehensive feedback
Overall Score (0-100): Holistic assessment of resume quality
ATS Compatibility Score: How well your resume works with Applicant Tracking Systems
Experience Level: Entry/Mid/Senior level classification
Strengths: What's working well in your resume
Weaknesses: Areas that need improvement
Missing Skills: Industry-standard skills you should consider adding
Improved Resume: AI-generated enhanced version with better formatting, stronger action verbs, and quantified achievements
Job Matches: Top 10 matching jobs from our database with compatibility scores
Download as PDF: One-click download of your improved resume

Stage 2: Job-Specific Analysis (Optional Deep Dive)

Analyze your resume against a specific job posting
Compatibility Score: How well you match this specific position
Skills Match: Detailed breakdown of matching vs missing skills
Gap Analysis: What you need to work on for this role
Tailoring Suggestions: Specific recommendations for this application
Job-Tailored Resume: Customized resume optimized for this specific job posting
Mock Interview Questions: Practice questions specific to this job role
Download Tailored PDF: Job-specific resume ready to submit

🔗 Live Application

Frontend Application: https://resumatch-frontend-hazel.vercel.app
Backend API: https://resumatch-backend-q5qo.onrender.com
API Health Check: https://resumatch-backend-q5qo.onrender.com/healthz
API Documentation: https://resumatch-backend-q5qo.onrender.com/docs

🚀 Quick Start

Visit the live application
Sign up as a Student or Recruiter
Students: Upload your resume and get AI-powered job matches
Recruiters: Post jobs and find qualified candidates
Use real-time chat to communicate with each other

✨ Features

For Students

📄 Two-Stage Resume Analysis:
- Stage 1 - Basic Analysis: Upload PDF resume and get immediate comprehensive feedback with overall score, ATS compatibility, experience level assessment, strengths, weaknesses, and missing skills
- Stage 2 - Job-Specific Analysis: Optional deep dive with job compatibility scoring, skill gap analysis, and tailored resume generation
✨ AI-Powered Resume Enhancement:
- Automatically generate improved resume with stronger action verbs, quantified achievements, and professional formatting
- Download improved resume as PDF with one click
🎯 Job-Tailored Resumes:
- Generate customized resumes optimized for specific job postings
- Reorder skills, rewrite experience bullets with job keywords, and highlight relevant achievements
- Download tailored resume as PDF for each job application
🎯 Smart Job Matching: Get top job recommendations based on resume analysis and skills with match percentages
💬 Real-time Chat: Communicate with recruiters through Socket.IO powered messaging
🎤 Mock Interviews: Practice with AI-generated interview questions tailored to your profile and specific jobs
📊 Application Tracking: Track job applications and their status

For Recruiters

📝 Job Posting: Create and manage job listings with detailed requirements
👥 Candidate Management: View and manage job applicants
💬 Direct Communication: Chat with potential candidates in real-time
🔍 Resume Screening: AI-assisted candidate evaluation and matching

Core Features

🔐 Secure Authentication: JWT-based auth with role-based access control
🌓 Dark/Light Mode: Toggle between themes for better user experience
📱 Responsive Design: Works seamlessly across desktop and mobile devices
⚡ Real-time Updates: Live notifications and messaging with Socket.IO

🛠️ Technology Stack

Backend

FastAPI - Modern Python web framework for building APIs
Socket.IO - Real-time bidirectional communication
MongoDB Atlas - Cloud database for storing user data, jobs, and messages
Groq Llama 3.3 70B - Advanced AI model for resume analysis, enhancement, and job matching
JWT - Secure authentication and authorization
PyPDF2 - PDF processing for resume text extraction
ReportLab - PDF generation for improved and tailored resumes
Uvicorn - ASGI server for FastAPI

Frontend

React 18 - Modern UI library with hooks and context
TypeScript - Type-safe JavaScript for better development experience
Vite - Fast build tool and development server
Tailwind CSS - Utility-first CSS framework for styling
Socket.IO Client - Real-time communication with backend
Axios - HTTP client for API calls
React Router - Client-side routing

DevOps & Deployment

Docker - Containerized application with multi-stage builds
Docker Hub - Image registry (josephshibumathew/resumatch)
Ubuntu VM - Production server deployment
Gunicorn - Python WSGI HTTP Server for production
Nginx - Reverse proxy and web server
UFW Firewall - Server security and port management
HTTPS/SSL - Secure connections with Let's Encrypt
SSH - Secure remote server access
Namecheap - Domain registration and DNS management (resumatchh.xyz)
Render - Alternative backend hosting platform
Vercel - Frontend hosting platform
GitHub - Version control and CI/CD
Environment Variables - Secure configuration management

📁 Project Structure

resumatch/
├── backend/                 # FastAPI Backend
│   ├── auth/               # Authentication & JWT handling
│   │   ├── auth_utils.py   # Password hashing, verification
│   │   ├── dependencies.py # Auth dependencies for routes
│   │   └── jwt_handler.py  # JWT token creation/validation
│   ├── database/           # Database connections
│   │   └── mongo.py        # MongoDB connection & collections
│   ├── models/             # Pydantic data models
│   │   ├── user.py         # User model (Student/Recruiter)
│   │   ├── job.py          # Job posting model
│   │   └── message.py      # Chat message model
│   ├── routes/             # API route handlers
│   │   ├── auth_routes.py  # Login, signup, logout
│   │   ├── student_routes.py # Resume upload, job matching
│   │   ├── recruiter_routes.py # Job posting, applicant management
│   │   ├── job_routes.py   # Job search, application
│   │   ├── pdf_generator.py # PDF generation for resumes
│   │   └── parser/         # AI & parsing utilities
│   │       ├── llama_client.py     # Groq Llama 3.3
│   │   └── chat_service.py # Chat management service
│   ├── sockets/            # Socket.IO handlers
│   │   ├── chat_server.py  # Real-time chat implementation
│   │   ├── chat_client.py  # Socket client for testing
│   │   └── chat_example.py # Usage examples
│   ├── utils/              # Utility functions
│   │   ├── password.py     # Password utilities
│   │   └── parser/         # AI & parsing utilities
│   │       ├── gemini_client.py    # Google Gemini AI integration
│   │       ├── resume_parser.py    # PDF text extraction
│   │       └── job_matcher.py      # Job matching algorithm
│   ├── scripts/            # Setup scripts
│   │   ├── setup_mongodb.py # Database initialization
│   │   └── setup_admin.py   # Admin user creation
│   ├── main.py             # FastAPI application entry point
│   ├── config.py           # Configuration settings
│   └── requirements.txt    # Python dependencies
│
├── frontend/               # React Frontend
│   ├── src/
│   │   ├── components/     # Reusable UI components
│   │   │   ├── Layout.tsx          # Main app layout
│   │   │   ├── LoadingSpinner.tsx  # Loading indicator
│   │   │   ├── ErrorBoundary.tsx   # Error handling
│   │   │   └── DarkModeToggle.tsx  # Theme switcher
│   │   ├── pages/          # Page components
│   │   │   ├── LoginPage.tsx       # User authentication
│   │   │   ├── SignupPage.tsx      # User registration
│   │   │   ├── StudentDashboard.tsx # Student main page
│   │   │   ├── RecruiterDashboard.tsx # Recruiter main page
│   │   │   ├── ResumeUploadPage.tsx # Resume analysis
│   │   │   ├── JobListPage.tsx     # Job search & browsing
│   │   │   ├── JobDetailsPage.tsx  # Individual job details
│   │   │   ├── ChatPage.tsx        # Real-time messaging
│   │   │   ├── MockInterviewPage.tsx # AI interview practice
│   │   │   ├── PostJobPage.tsx     # Job creation (recruiters)
│   │   │   └── MyJobsPage.tsx      # Job management
│   │   ├── services/       # API communication
│   │   │   ├── api.ts              # Axios configuration
│   │   │   ├── authService.ts      # Authentication API
│   │   │   ├── studentService.ts   # Student-specific API
│   │   │   ├── recruiterService.ts # Recruiter-specific API
│   │   │   ├── jobService.ts       # Job-related API
│   │   │   ├── resumeService.ts    # Resume analysis API
│   │   │   └── chatService.ts      # Chat/messaging API
│   │   ├── context/        # React Context providers
│   │   │   ├── AuthContext.tsx     # Authentication state
│   │   │   ├── ThemeContext.tsx    # Dark/light mode
│   │   │   └── ChatContext.tsx     # Chat state management
│   │   ├── hooks/          # Custom React hooks
│   │   │   ├── useApi.ts           # API calling hook
│   │   │   ├── useLoading.ts       # Loading state hook
│   │   │   └── useJobs.ts          # Job data hook
│   │   ├── types/          # TypeScript type definitions
│   │   │   └── index.ts            # All type definitions
│   │   └── utils/          # Utility functions
│   │       ├── auth.ts             # Auth helper functions
│   │       └── helpers.ts          # General utilities
│   ├── public/             # Static assets
│   ├── package.json        # Node.js dependencies
│   ├── vite.config.ts      # Vite configuration
│   ├── tailwind.config.js  # Tailwind CSS configuration
│   └── tsconfig.json       # TypeScript configuration
│
├── docker/                 # Docker configuration
│   ├── docker-compose.yml       # Development (default)
│   ├── docker-compose.dev.yml   # Development (explicit)
│   ├── docker-compose.prod.yml  # Production
│   ├── .dockerignore           # Docker ignore rules
│   └── README.md               # Docker documentation
│
├── env/                    # Environment configuration
│   ├── .env.dev           # Development environment variables
│   ├── .env.prod          # Production environment template
│   └── README.md          # Environment documentation
│
├── scripts/               # Automation scripts
│   ├── Makefile          # Command shortcuts
│   ├── deploy-production.sh  # Production deployment script
│   ├── verify-setup.sh       # Environment verification
│   └── README.md             # Scripts documentation
│
├── docs/                  # Project documentation
│   ├── DOCKER_*.md       # Docker guides
│   ├── PRODUCTION_DEPLOYMENT.md
│   └── ...               # Other documentation
│
├── .gitignore             # Git ignore rules
├── .env                   # Active environment (not in git)
└── README.md              # This file

🚀 Quick Deployment Guide

Prerequisites

MongoDB Atlas account (free tier available)
Groq API account (free tier with generous limits - console.groq.com)
Domain name (optional - we use Namecheap for resumatchh.xyz)
Ubuntu VM or cloud server (for production deployment)
Docker installed (for containerized deployment)

Deployment Options

This project supports three deployment strategies:

1. 🐳 Docker Deployment (Recommended for Development)

Full containerization with Docker Compose for easy local development and testing.

# From project root, navigate to scripts folder
cd scripts

# Development environment (with hot-reload)
make dev-up

# Production environment (optimized images)
make prod-up

See detailed guides:

Docker Configuration - Docker files documentation
Docker Quick Start Guide
Docker Deployment Guide
Docker Quick Reference

2. 🖥️ Ubuntu VM Production Deployment (Current Production)

Enterprise-grade deployment on Ubuntu server with Gunicorn, Nginx, HTTPS, and security hardening.

Production URL: https://resumatchh.xyz

Features:

✅ Ubuntu 20.04/22.04 LTS server
✅ Gunicorn WSGI server with multiple workers
✅ Nginx reverse proxy with SSL/TLS
✅ HTTPS encryption with Let's Encrypt
✅ SSH secure access
✅ UFW firewall configuration
✅ Custom domain (resumatchh.xyz via Namecheap)
✅ Automated SSL certificate renewal
✅ Process monitoring and auto-restart

See detailed guide:

Production Deployment Guide

3. ☁️ Cloud Platform Deployment (Vercel + Render)

Quick deployment using managed cloud platforms.

Live URLs:

Frontend: https://resumatch-front-4nts.vercel.app
Backend: https://resumatch-backend-q5qo.onrender.com

Prerequisites

Prerequisites (Continued)

Render account (for managed backend deployment)
Vercel account (for managed frontend deployment)

AI Capabilities Powered by Llama 3.3 70B

The platform includes four specialized AI functions:

analyze_resume_basic() - Comprehensive resume scoring and feedback
generate_improved_resume() - Creates enhanced version with better formatting and language
analyze_job_fit() - Job-specific compatibility analysis and gap assessment
generate_job_tailored_resume() - Creates customized resume for specific job postings

1. Clone and Setup

git clone https://github.com/bipaulr/ResuMatch.git
cd ResuMatch

2. Backend Deployment (Render)

Connect this repository to Render
Create Web Service with these settings:
- Root Directory: backend
- Build Command: pip install -r requirements.txt
- Start Command: uvicorn main:api --host 0.0.0.0 --port $PORT

Add environment variables:

MONGODB_URI=your_mongodb_atlas_connection_string
JWT_SECRET=your_secure_random_secret
GOOGLE_API_KEY=your_google_gemini_api_key
ALLOWED_ORIGINS=https://your-frontend.vercel.app

3. Frontend Deployment (Vercel)

Connect this repository to Vercel
Set root directory to frontend

Add environment variables:

VITE_API_BASE_URL=https://your-backend.onrender.com
VITE_SOCKET_PATH=/ws/socket.io

4. Database Setup (MongoDB Atlas)

Create free M0 cluster
Create database user
Add network access (0.0.0.0/0 for deployment)
Get connection string

5. AI Setup (Google Gemini)

Visit Google AI Studio
Create API key
Add to backend environment variables

🔧 Environment Variables

Backend (.env)

# Server Configuration
ALLOWED_ORIGINS=http://localhost:5173,https://your-frontend-domain.vercel.app
JWT_SECRET=your_super_secret_jwt_key_change_this_in_production
JWT_EXPIRES_IN=86400

# Database
MONGODB_URI=mongodb+srv://username:password@cluster.mongodb.net/resumatch?retryWrites=true&w=majority

# AI Configuration
GROQ_API_KEY=your_groq_api_key_from_console_groq_com
GROQ_MODEL=llama-3.3-70b-versatile

Frontend (.env.local)

# API Configuration
VITE_API_BASE_URL=http://localhost:8000
VITE_SOCKET_PATH=/ws/socket.io

Production Environment Variables

Render (Backend):

ALLOWED_ORIGINS: Your Vercel domain(s)
MONGODB_URI: MongoDB Atlas connection string
JWT_SECRET: Strong secret key
GROQ_API_KEY: Groq API key from console.groq.com

Vercel (Frontend):

VITE_API_BASE_URL: Your Render backend URL
VITE_SOCKET_PATH: /ws/socket.io

📚 API Documentation

Authentication Endpoints

POST /auth/signup - Register new user
POST /auth/login - User login
GET /auth/me - Get current user info

Student Endpoints (Stage 1 - Basic Analysis with immediate comprehensive feedback, improved resume generation, and job matches)

POST /student/analyze-resume - Job-specific analysis (Stage 2 - Advanced Analysis with compatibility scoring, gap analysis, and tailored resume generation)
GET /student/download-improved-resume - Download AI-enhanced resume as PDF
GET /student/download-tailored-resume - Download job-tailored resume as PDF
POST /student/upload-resume - Upload and analyze resume
GET /student/job-matches - Get matched jobs
POST /student/apply/{job_id} - Apply to a job
GET /student/applications - Get user's applications

Recruiter Endpoints

POST /recruiter/jobs - Create new job posting
GET /recruiter/jobs - Get recruiter's jobs
GET /recruiter/jobs/{job_id}/applicants - Get job applicants

Job Endpoints

GET /jobs - Search and filter jobs
GET /jobs/{job_id} - Get job details

Chat Endpoints

GET /chat/messages/{room_id} - Get chat history
WebSocket: /ws/socket.io - Real-time messaging

🚢 Deployment Guide

Step 1: MongoDB Atlas Setup

Create free MongoDB Atlas account
Create a new cluster (M0 free tier)
Create datroq API Setup (Llama 3.3 70B)
Visit Groq Console
Create free account and generate API key
Update GROQ_API_KEY in environment variables
Model used: llama-3.3-70b-versatile (fast and powerful)
Create Google Cloud project
Enable Gemini API
Create API key
Update GOOGLE_API_KEY in environment variables

Step 3: Backend Deployment (Render)

Push code to GitHub
Create new Web Service on Render
Connect GitHub repository
Set root directory to backend
Set build command: pip install -r requirements.txt
Set start command: uvicorn main:api --host 0.0.0.0 --port $PORT
Add environment variables
Deploy and test /healthz endpoint

Step 4: Frontend Deployment (Vercel)

Create new project on Vercel
Connect GitHub repository
Set root directory to frontend
Set build command: npm run build
Set output directory: dist
Add environment variables
Deploy and test the application

Step 5: Final Configuration

Update ALLOWED_ORIGINS in Render with your Vercel domain
Update VITE_API_BASE_URL in Vercel with your Render domain
Test complete workflow: signup → login → resume upload → job matching → chat

👥 User Workflows

Student Journey

Sign Up/Login → Create account with student role
Upload Resume → PDF analysis with AI skill extraction and immediate comprehensive feedback
Get Instant Value → View overall score, ATS compatibility, strengths, weaknesses, and missing skills
Download Improved Resume → Get AI-enhanced resume with better formatting and stronger language
Optional Deep Analysis → Run job-specific analysis for positions you're interested in
Get Tailored Resume → Download customized resume optimized for specific job postings
View Job Matches → Get top recommended jobs based on skills with match percentages
Browse Jobs → Search and filter available positions
Apply to Jobs → Submit applications with one click
Chat with Recruiters → Real-time communication
Mock Interview → Practice with AI-generated questions tailored to specific jobs
Track Applications → Monitor application status

Recruiter Journey

Sign Up/Login → Create account with recruiter role
Post Jobs → Create detailed job listings with requirements
Manage Listings → View and edit posted jobs
Review Applicants → See candidate profiles and resumes
Chat with Candidates → Direct communication with applicants
Evaluate Candidates → AI-assisted matching and with PyPDF2
Stage 1 AI Analysis: Groq Llama 3.3 70B for comprehensive resume scoring, skill extraction, and improvement generation
Stage 2 AI Analysis: Job-specific compatibility scoring, gap analysis, and tailored resume generation
PDF Generation: ReportLab for creating downloadable improved and tailored resumes
Real-time Chat: Socket.IO for instant messaging
Data Persistence: MongoDB for all user data, resumes, and analysis result
File Upload: PDF processing and text extraction
AI Analysis: Gemini API for skill extraction and matching
Real-time Chat: Socket.IO for instant messaging
Data Persistence: MongoDB for all user data and relationships

🤝 Contributing

Fork the repository
Create feature branch (git checkout -b feature/amazing-feature)
Commit changes (git commit -m 'Add amazing feature')
Push to branch (git push origin feature/amazing-feature)
Open Pull Request

📄 License

This project is licensed under the MIT License.

🐛 Known Issues & Troubleshooting

Common Issues

CORS Errors: Ensure ALLOWED_ORIGINS includes your frontend domain
Socket.IO Connection: Check VITE_SOCKET_PATH matches backend mount point
File Upload: Verify PDF files are valid and readable
AI Responses: Check Google API key and quota limits

Support

Create an issue on GitHub for bugs
Check API documentation at /docs endpoint
Verify environment variables are correctly set

Built with ❤️ by the ResuMatch Team

Name		Name	Last commit message	Last commit date
backend		backend
docker		docker
docs		docs
env		env
frontend		frontend
scripts		scripts
.gitignore		.gitignore
README.md		README.md
requirements.txt		requirements.txt

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ResuMatch - AI-Powered Resume-Job Matching Platform

🎯 Try It Now

🌐 Live Demo

📋 Test Features:

🔧 API Access

📋 Table of Contents

🌟 Overview

🎯 New Two-Stage Resume Analysis System

🔗 Live Application

🚀 Quick Start

✨ Features

For Students

For Recruiters

Core Features

🛠️ Technology Stack

Backend

Frontend

DevOps & Deployment

📁 Project Structure

🚀 Quick Deployment Guide

Prerequisites

Deployment Options

1. 🐳 Docker Deployment (Recommended for Development)

2. 🖥️ Ubuntu VM Production Deployment (Current Production)

3. ☁️ Cloud Platform Deployment (Vercel + Render)

Prerequisites

Prerequisites (Continued)

AI Capabilities Powered by Llama 3.3 70B

1. Clone and Setup

2. Backend Deployment (Render)

3. Frontend Deployment (Vercel)

4. Database Setup (MongoDB Atlas)

5. AI Setup (Google Gemini)

🔧 Environment Variables

Backend (.env)

Frontend (.env.local)

Production Environment Variables

📚 API Documentation

Authentication Endpoints

Student Endpoints (Stage 1 - Basic Analysis with immediate comprehensive feedback, improved resume generation, and job matches)

Recruiter Endpoints

Job Endpoints

Chat Endpoints

🚢 Deployment Guide

Step 1: MongoDB Atlas Setup

Step 3: Backend Deployment (Render)

Step 4: Frontend Deployment (Vercel)

Step 5: Final Configuration

👥 User Workflows

Student Journey

Recruiter Journey

🤝 Contributing

📄 License

🐛 Known Issues & Troubleshooting

Common Issues

Support

About

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Watchers

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